ljrk {ljr}

MLE with k joinpoints

Description

Determines the maximum likelihood estimates of model coefficients in the logistic joinpoint regression model with k joinpoints.

Usage

ljrk(k,y,n,tm,X,ofst)

Arguments

k

the pre-specified number of joinpoints (with unknown locations).

y

the vector of Binomial responses.

n

the vector of sizes for the Binomial random variables.

tm

the vector of ordered observation times.

X

a design matrix containing other covariates.

ofst

a vector of known offsets for the logit of the response.

Details

The re-weighted log-likelihood is the log-likelihood divided by the largest component of n.

Value

Coef

A table of coefficient estimates.

Joinpoints

The estimates of the joinpoints.

wlik

The maximum value of the re-weighted log-likelihood.

Author(s)

The authors are Michal Czajkowski, Ryan Gill, and Greg Rempala. The software is maintained by Ryan Gill [e-mail].

References

Czajkowski, M., Gill, R. and Rempala, G. (2008). Model selection in logistic joinpoint regression with applications to analyzing cohort mortality patterns. Statistics in Medicine 27, 1508-1526.

See Also

ljrb,ljrf

Examples

 data(kcm)
 attach(kcm) 
 ljrk(1,Count,Population,Year+.5)